1. Field
One or more embodiments of the present invention relate to a mobile robot, and more particularly, to system, method and medium calibrating a gyrosensor (gyroscope sensor) of a mobile robot.
2. Description of the Related Art
Robots or robotic devices have been developed for a variety of tasks including industrial purposes and for factory automation. Robots have also been used to perform tasks in extreme environments that human beings cannot access. Robotics has been rapidly developed as applied to the cutting-edge space development industry. Recently, even human-friendly household robots have been developed. In addition, robots have been inserted into human bodies and used to heal delicate human tissue, which was at times not possible using conventional medical devices. Such developments have drawn a lot of attention to robotics as a cutting-edge field that may soon replace other cutting-edge fields such as biotechnology and the information revolution initiated by the introduction of the Internet.
In particular, household robots have played a major role in evolving heavy industry-centered robotics, which is limited to the development of industrial robots, to light industry-centered robotics. A typical example of household robots includes cleaning robots. A cleaning robot includes a driving unit moving the cleaning robot, a cleaning unit for a cleaning operation, and a location measurement unit measuring the location of the cleaning robot or a user's remote control.
The most basic and important function of a mobile robot such as a cleaning robot, is to accurately identify its location. Techniques for calculating the absolute location of a mobile robot include a technique of implementing a beacon, which employs an ultrasonic sensor, at home and a technique using an indoor global positioning system (GPS). In addition, a technique for calculating the relative location of a mobile robot includes a technique for calculating the location of a mobile robot by obtaining the rotational velocity (angular velocity) and linear velocity of the mobile robot from an encoder and integrating the rotational velocity and the rectilinear velocity, a technique for calculating the location of a mobile robot by integrating an accelerated velocity, which is obtained from an acceleration sensor, twice and a technique for calculating the direction of a mobile robot by integrating a rotation velocity output from a gyrosensor.
A gyrosensor measures angular velocity. If the measured angular velocity is integrated once with respect to time, an angle of direction of a mobile robot can be measured. The gyrosensor calculating the location of the mobile robot may be resistant to its surrounding environment and implemented as a stand-alone device. In order to obtain accurate measurement values using the gyrosensor, correcting the bias drift of the gyrosensor and calibration of the gyrosensor must also be performed.
A bias drift denotes a variation in the signal level of a gyrosensor over time when a mobile robot is not moving, and calibration denotes mapping a signal level of raw data obtained from the gyrosensor to a real physical value (angular velocity), that is, obtaining a scale factor.
In order to correct the bias drift of a gyrosensor, a simple technique for correcting a current signal level using a signal level obtained when a mobile robot is not moving is generally used. However, no general technique for calibrating the gyrosensor is available, other than techniques using a data sheet or a rotary table.
The data sheet is a table reflecting the relationship between raw data and angular velocity, which is intermittently created by a manufacturer of a gyrosensor after conducting experiments. However, since the data sheet is created under specific conditions, it fails to take into consideration the aging of the gyrosensor or a change in scale factor according to an external temperature change.
FIG. 1 illustrates a conventional mobile robot 10 to which a conventional calibration technique using a rotary table is applied. The mobile robot 10 includes a gyrosensor 11, a jig 13, and a processing module 12. The gyrosensor 11 measures rotary inertia and outputs raw data. The jig 13 includes a rotary table rotating the mobile robot 10 and measures the angular velocity of the rotary table. The processing module 12 calculates a scale factor of the raw data based on the measured angular velocity and provides the scale factor to the gyrosensor 11.
Some of the drawbacks of the conventional mobile robot 10 are that it requires an expensive jig 13 and that calibration cannot be performed in real time while the mobile robot 10 is moving since the mobile robot 10 has to be first loaded into the jig 13 before calibration.